mne.simulation.metrics.recall_score#
- mne.simulation.metrics.recall_score(stc_true, stc_est, threshold='90%', per_sample=True)[source]#
Compute the recall.
The recall is the ratio
tp / (tp + fn)
wheretp
is the number of true positives andfn
the number of false negatives. The recall is intuitively the ability of the classifier to find all the positive samples.The best value is 1 and the worst value is 0.
Threshold is used first for data binarization.
- Parameters:
- stc_trueinstance of (Vol|Mixed)SourceEstimate
The source estimates containing correct values.
- stc_estinstance of (Vol|Mixed)SourceEstimate
The source estimates containing estimated values e.g. obtained with a source imaging method.
- threshold
float
|str
The threshold to apply to source estimates before computing the recall. If a string the threshold is a percentage and it should end with the percent character.
- per_sample
bool
If True the metric is computed for each sample separately. If False, the metric is spatio-temporal.
- Returns:
Notes
New in version 1.2.
Examples using mne.simulation.metrics.recall_score
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Compare simulated and estimated source activity